In December 2008, Luis Bettencourt and David Kaiser reported their findings[1] from studies of research collaboration networks, which included their discovery that, as coauthorship networks in a particular field reach the point of forming a single giant component of interconnected authors that dwarfs all other coauthor groups in that field, the growth near that point depends in a universal way on the average number of coauthors per author.In particular, the fraction of coauthor links that belong to the giant component appears to be proportional to ( - kc)0.35, where kc, which marks the critical point, depends on the research field.[2]The remarkable fact is that the exponent, 0.35, fits the data for networks in several quite distinct fields.This value apparently isn’t common to networks in general, though.I had wondered what features of a network do determine the exponent’s value.

I can’t remember how it went now, but as a child I skipped rope to a rhyme that included “would I, could I” somewhere in it.Recently questions were asked about OSTI’s involvement with scientific research data.Is OSTI planning to become a repository for numeric data?Are we going to issue Digital Object Identifiers (DOIs) for datasets, and would we be telling people how to manage their data?For some reason, the questions triggered the memory of that old refrain, but now I was thinking from an OSTI perspective, “would we, could we…?”

Science.gov has an updated look this week to make room for enhancements. The enhancements will both faciliate use and awareness of Science.gov and highlight findings and activities of the participating agencies.

Want to share or save a permanent link on Science.gov via social networking sites such as Twitter and Facebook? There is now a sharing and bookmarking toolbar on the main Science.gov page as well as on each subject page .

As with most things, all federated search products are not created equally. Recently, I ran across a situation where federated search was derided for lack of capability related to precision search and relevancy ranking. As is often the case, this derision is founded in a narrow view of federated search. The view that federated search is only capable of generically searching data stores or not providing relevance across the resources being searched is this narrow view of what the technology can achieve.